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experimental segmoe support

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Vladimir Mandic
2024-02-05 10:38:42 -05:00
parent ff2c1db1cc
commit e32220ccc1
13 changed files with 1376 additions and 15 deletions
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modules/processing_diffusers.py
+7 -4
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@@ -158,7 +158,9 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
if hasattr(model, "set_progress_bar_config"):
model.set_progress_bar_config(bar_format='Progress {rate_fmt}{postfix} {bar} {percentage:3.0f}% {n_fmt}/{total_fmt} {elapsed} {remaining} ' + '\x1b[38;5;71m' + desc, ncols=80, colour='#327fba')
args = {}
signature = inspect.signature(type(model).__call__)
if hasattr(model, 'pipe'): # recurse
model = model.pipe
signature = inspect.signature(type(model).__call__, follow_wrapped=True)
possible = signature.parameters.keys()
debug(f'Diffusers pipeline possible: {possible}')
if shared.opts.diffusers_generator_device == "Unset":
@@ -201,14 +203,15 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
if 'generator' in possible and generator is not None:
args['generator'] = generator
if 'output_type' in possible:
args['output_type'] = 'np'
if hasattr(model, 'vae'):
args['output_type'] = 'np' # only set latent if model has vae
if 'callback_steps' in possible:
args['callback_steps'] = 1
if 'callback' in possible:
args['callback'] = diffusers_callback_legacy
elif 'callback_on_step_end_tensor_inputs' in possible:
args['callback_on_step_end'] = diffusers_callback
if 'prompt_embeds' in possible and 'negative_prompt_embeds' in possible:
if 'prompt_embeds' in possible and 'negative_prompt_embeds' in possible and hasattr(model, '_callback_tensor_inputs'):
args['callback_on_step_end_tensor_inputs'] = model._callback_tensor_inputs # pylint: disable=protected-access
else:
args['callback_on_step_end_tensor_inputs'] = ['latents']
@@ -405,7 +408,7 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
desc='Base',
)
update_sampler(shared.sd_model)
shared.state.sampling_steps = base_args['num_inference_steps']
shared.state.sampling_steps = base_args.get('num_inference_steps', p.steps)
p.extra_generation_params['Pipeline'] = shared.sd_model.__class__.__name__
if shared.opts.scheduler_eta is not None and shared.opts.scheduler_eta > 0 and shared.opts.scheduler_eta < 1:
p.extra_generation_params["Sampler Eta"] = shared.opts.scheduler_eta